StringTools[Entropy] - compute the Entropy of a string
|
Calling Sequence
|
|
Entropy( s )
|
|
Description
|
|
•
|
The Entropy(s) command returns the Shannon entropy of the string s. A floating-point number, the entropy of the string, is returned.
|
•
|
Shannon's entropy is defined as -add( P( ch ) * log[ 2 ]( P( ch ) ), ch = Support( s ) ), where . It is a measure of the information content of the string, and can be interpreted as the number of bits required to encode each character of the string given perfect compression. The entropy is maximal when each character is equally likely. For arbitrary non-nul characters, this maximal value is .
|
|
(The nul byte, with code point , cannot appear in a Maple string. If all 256 single byte code points could appear, then the maximal entropy would be , which is the number of bits per byte).
|
•
|
Note that the entropy is computed as a floating-point number, at hardware (double) precision.
|
|
|
Examples
|
|
>
|
|
| (1) |
>
|
|
>
|
|
| (2) |
>
|
|
| (3) |
>
|
|
| (4) |
>
|
|
| (5) |
>
|
|
| (6) |
>
|
|
| (7) |
>
|
|
| (8) |
>
|
|
| (9) |
>
|
|
| (10) |
>
|
|
| (11) |
>
|
|
| (12) |
The following steps illustrate the definition of Entropy.
>
|
|
| (13) |
>
|
|
| (14) |
>
|
|
| (15) |
>
|
|
| (16) |
>
|
|
| (17) |
>
|
|
| (18) |
|
|
See Also
|
|
add, convert, evalf, length, log, map, seq, string, StringTools, StringTools[CountCharacterOccurrences], StringTools[Iota], StringTools[Random], StringTools[Repeat], StringTools[Support], with
|
|
Download Help Document
Was this information helpful?